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By combining high-resolution image-based phenotyping with functional mapping and genome prediction, a new study has provided insights into the complex genetic architecture and molecular mechanisms underlying early shoot growth dynamics in rice.

The more rapidly leaves of a plant emerge and create canopy closure, the more successful the plant, in establishment, resource acquisition and ultimately yield. An early vigor trait is particularly important in aerobic rice environments, which are highly susceptible to water deficits. The timing of developmental ‘triggers’ or switches that initiate tiller formation and rapid exponential growth are a critical component of this trait, however, searching for the switch that initiates this growth has proven challenging due to the complex genetic basis and large genotype-by-environment effect, and the difficulty in accurately measuring shoot growth for large populations.

“The availability of large, automated phenotyping platforms, such as those at Australian Plant Phenomics Facility (APPF), allow plants to be non-destructively phenotyped throughout the lifecycle in a controlled environment, and provide high resolution temporal data that can be used to examine these important developmental switches,” said PhD student, Malachy Campbell.

Malachy and team, including Bettina Berger and Chris Brien from the APPF, phenotyped a panel of ~360 diverse rice accessions throughout the vegetative stage (11-44 day old plants) at The Plant Accelerator® at APPF. A mathematical equation was used to describe temporal growth trajectories of each accession. Regions of the genome that may regulate early vigor were inferred using genome-wide association (GWA) mapping. However, many loci with small effects on shoot growth trajectories were identified, indicating that many genes contribute to this trait. GWA, together with RNA sequencing identified a gibberellic acid (GA) catabolic gene, OsGA2ox7, which could be influencing GA levels to regulate vigor in the early tillering stage.

Dr Malachy Campell in The Plant Accelerator® at the Australian Plant Phenomics Facility’s Adelaide node

For some traits where genetic variation is controlled by a small number of loci, breeders can use MAS to identify individuals carrying the favourable locus/loci for the given trait, and select them for the next generation. For complex traits that are regulated by many loci, it becomes very difficult to detect loci that are associated with the trait. However, an alternative approach, genomic selection (GS), considers the total genetic contribution of all loci to the given trait. With this approach, loci across the genome can be used to predict the performance of individuals that have not yet been phenotyped (i.e. those in future generations). Since many loci were found to be contributing to early vigor, the team explored the possibility of using GS for improving this trait. Shoot growth trajectories could be predicted with reasonable accuracy, with greater accuracies being achieved when a higher number of markers were used. These results suggest that GS may be an effective strategy for improving shoot growth dynamics during the vegetative growth stage in rice. The approach of combining high-resolution image-based phenotyping, functional mapping and genome prediction could be widely applicable for complex traits across numerous crop species.

Read the full paper, published in The Plant Genome, here. (doi:10.3835/plantgenome2016.07.0064).

The C4 Rice Consortium coordinates efforts from labs all over the world trying to isolate the genes responsible in C4 plants and apply them in C3 plants. If successful, yields in wheat and rice are expected to be 50% higher than present. An impressive result seen as vital for future food security. The consortium is led by Jane Langdale at the University of Oxford and funded by the Bill & Melinda Gates Foundation.

A recent study has collected phenotypic data of chickpea (Cicer arietinum L.) which can now be linked with the genotypic data of these lines. This will enable genome-wide association mapping with the aim of identifying loci that underlie salinity tolerance – an important step in developing salt tolerant chickpeas.

In this study, Judith Atieno and co-authors utilised image-based phenotyping at the Australian Plant Phenomics Facility to study genetic variation in chickpea for salinity tolerance in 245 diverse accessions (a diversity collection, known as the Chickpea Reference Set).

Chickpea is an important legume crop, used as a highly nutritious food source and grown in rotation with cereal crops to fix nitrogen in the soil or to act as a disease break. However, despite its sensitivity to salt, chickpea is generally grown in semi-arid regions which can be prone to soil salinity. This results in an estimated global annual chickpea yield loss of between 8–10%.

Salinity tolerance phenotyping in a Smarthouse at the Australian Plant Phenomics Facility’s Adelaide node at the Waite Research Precinct – Plants were imaged at 28 DAS for 3 consecutive days prior to 40 mM NaCl application in two increments over 2 days. Plants were daily imaged until 56 DAS. Right pane shows 6-week-old chickpeas on conveyor belts leaving the imaging hall proceeding to an automatic weighing and watering station.

The study found, on average, salinity reduced plant growth rate (obtained from tracking leaf expansion through time) by 20%, plant height by 15% and shoot biomass by 28%. Additionally, salinity induced pod abortion and inhibited pod filling, which consequently reduced seed number and seed yield by 16% and 32%, respectively. Importantly, moderate to strong correlation was observed for different traits measured between glasshouse and two field sites indicating that the glasshouse assays are relevant to field performance. Using image-based phenotyping, we measured plant growth rate under salinity and subsequently elucidated the role of shoot ion independent stress (resulting from hydraulic resistance and osmotic stress) in chickpea. Broad genetic variation for salinity tolerance was observed in the diversity panel with seed number being the major determinant for salinity tolerance measured as yield. The study proposes seed number as a selection trait in breeding salt tolerant chickpea cultivars.

Genotypic variation for salinity tolerance in the Chickpea Reference Set. Varying levels of salinity tolerance exhibited by different chickpea genotypes. Exposure of sensitive genotypes to 40 mM NaCl caused severe stunted growth, leaf damage, and led to less number of reproductive sites (flowers and pods) compared to moderately tolerant and tolerant genotypes.

The rapid development of new, high-resolution and high-throughput phenotyping technologies in plant science has provided the opportunity to more deeply explore genetic variation for salinity tolerance in crop species and identify traits that are potentially novel and relevant to yield improvement. The Australian Plant Phenomics Facility provides state-of-the-art phenotyping and analytical tools and expertise in controlled environments and in the field to help academic and commercial plant scientists understand and relate the performance of plants to their genetic make-up. A dedicated cross-disciplinary team of experts provides consultation on project design and high quality support.

To read the full paper in Scientific Reports,“Exploring genetic variation for salinity tolerance in chickpea using image-based phenotyping” (doi:10.1038/s41598-017-01211-7), click here.

To find out more about the Australian Plant Phenomics Facility and how we can support your researchclick here.

With a rapidly growing population, improving the yield of global food staples such as rice has become an urgent focus for plant scientists.

In a recent study published on Plant Physiology, scientists have discovered they can improve rice productivity by selecting rice varieties that are better at capturing sunlight to produce grains instead of reflecting it as heat.

“We studied hundreds of plants from five rice cultivars and found that there is variation between these varieties in relation to the quantity of light they use for growth or dissipate as heat. Some of them are capable of converting more sunlight into chemical energy, producing greater leaf area over time,” said lead researcher, Dr Katherine Meacham.

When leaves intercept sunlight, this sunlight is either; 1) absorbed by the leaf and converted via the process of photosynthesis into the plants own components; leaves, grains, roots, etc. 2) dissipated as heat as an strategy to protect the proteins of the plant from sun damage (photo-protection) or, 3) re-emitted as fluorescent light. In this study, the researchers measured fluorescence to infer the quantity of energy that is either converted into food or dissipated as heat.

“What is new about our research is that scientists had previously thought there was not much variation in how efficiently leaves could absorb and use light, and the reason for this is that they were not considering the full picture and measuring the plants throughout the entire day under natural illumination. We revealed that there are considerable differences between the five rice cultivars under moderate light and that means that there is room for selecting the most efficient plants,” said Professor Furbank.

“We found that there is room for improvement in some cultivars that can result in more photosynthesis without risking the plant’s protection strategies against sunlight damage.

The scientists measured fluorescence by clipping light receptors on leaves throughout a whole day to get a full picture of how the plant uses sunlight.

Traditional breeding for photosynthetic traits has not been a common strategy in any major cereal crop, in part due to the difficulty in measuring photosynthesis in thousands of plants. However, rapid screening tools are now available to study the interaction between the genes and the way they interact with the environment.

“Using unique facilities at the Australian Plant Phenomics Facility’s High Resolution Plant Phenomics Centre we were able to follow chlorophyll fluorescence in rice canopies throughout the entire day under natural illumination. This gave us completely different results when compared to the usual 30 min measurement of leaf level light use efficiency. By combining this with digital biomass analysis using PlantScan, we could link light use efficiency with growth, revealing genetic variation in rice varieties not previously detected,” said Professor Furbank.

“Our next step is to find varieties with superior photo-protection. We can directly use these for breeding and find the genes responsible. We have the capacity to screen many thousands of rice varieties for which we have gene sequence through the International Rice Research Institute,” said Dr Meacham.